numpy.random.Generator.beta#
method
- random.Generator.beta(a, b, size=None)#
Draw samples from a Beta distribution.
The Beta distribution is a special case of the Dirichlet distribution, and is related to the Gamma distribution. It has the probability distribution function
\[f(x; a,b) = \frac{1}{B(\alpha, \beta)} x^{\alpha - 1} (1 - x)^{\beta - 1},\]where the normalization, B, is the beta function,
\[B(\alpha, \beta) = \int_0^1 t^{\alpha - 1} (1 - t)^{\beta - 1} dt.\]It is often seen in Bayesian inference and order statistics.
- Parameters
- afloat or array_like of floats
Alpha, positive (>0).
- bfloat or array_like of floats
Beta, positive (>0).
- sizeint or tuple of ints, optional
Output shape. If the given shape is, e.g.,
(m, n, k), thenm * n * ksamples are drawn. If size isNone(default), a single value is returned ifaandbare both scalars. Otherwise,np.broadcast(a, b).sizesamples are drawn.
- Returns
- outndarray or scalar
Drawn samples from the parameterized beta distribution.